{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1 align=\"center\">tqdm</h1>\n",
    "<img src=\"https://img.tqdm.ml/logo.gif\" align=\"left\" />\n",
    "\n",
    "[![Py-Versions](https://img.shields.io/pypi/pyversions/tqdm.svg?logo=python&logoColor=white)](https://pypi.org/project/tqdm)|[![Versions](https://img.shields.io/pypi/v/tqdm.svg)](https://tqdm.github.io/releases)|[![Conda-Forge-Status](https://img.shields.io/conda/v/conda-forge/tqdm.svg?label=conda-forge&logo=conda-forge)](https://anaconda.org/conda-forge/tqdm)|[![Docker](https://img.shields.io/badge/docker-pull-blue.svg?logo=docker&logoColor=white)](https://hub.docker.com/r/tqdm/tqdm)|[![Snapcraft](https://img.shields.io/badge/snap-install-82BEA0.svg?logo=snapcraft)](https://snapcraft.io/tqdm)\n",
    "-|-|-|-|-\n",
    "\n",
    "[![Build-Status](https://img.shields.io/github/workflow/status/tqdm/tqdm/Test/master?logo=GitHub)](https://github.com/tqdm/tqdm/actions?query=workflow%3ATest)|[![Coverage-Status](https://img.shields.io/coveralls/github/tqdm/tqdm/master?logo=coveralls)](https://coveralls.io/github/tqdm/tqdm)|[![Branch-Coverage-Status](https://codecov.io/gh/tqdm/tqdm/branch/master/graph/badge.svg)](https://codecov.io/gh/tqdm/tqdm)|[![Codacy-Grade](https://app.codacy.com/project/badge/Grade/3f965571598f44549c7818f29cdcf177)](https://www.codacy.com/gh/tqdm/tqdm/dashboard)|[![Libraries-Rank](https://img.shields.io/librariesio/sourcerank/pypi/tqdm.svg?logo=koding&logoColor=white)](https://libraries.io/pypi/tqdm)|[![PyPI-Downloads](https://img.shields.io/pypi/dm/tqdm.svg?label=pypi%20downloads&logo=PyPI&logoColor=white)](https://pepy.tech/project/tqdm)\n",
    "-|-|-|-|-|-\n",
    "\n",
    "[![DOI](https://img.shields.io/badge/DOI-10.5281/zenodo.595120-blue.svg)](https://doi.org/10.5281/zenodo.595120)|[![LICENCE](https://img.shields.io/pypi/l/tqdm.svg)](https://raw.githubusercontent.com/tqdm/tqdm/master/LICENCE)|[![OpenHub-Status](https://www.openhub.net/p/tqdm/widgets/project_thin_badge?format=gif)](https://www.openhub.net/p/tqdm?ref=Thin+badge)|[![binder-demo](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/tqdm/tqdm/master?filepath=DEMO.ipynb)|[![awesome-python](https://awesome.re/mentioned-badge.svg)](https://github.com/vinta/awesome-python)\n",
    "-|-|-|-|-\n",
    "\n",
    "`tqdm` derives from the Arabic word *taqaddum* (تقدّم) which can mean\n",
    "\"progress,\" and is an abbreviation for \"I love you so much\" in Spanish\n",
    "(*te quiero demasiado*).\n",
    "\n",
    "Instantly make your loops show a smart progress meter - just wrap any\n",
    "iterable with `tqdm(iterable)`, and you're done!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "for i in tqdm(range(10000)):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`trange(N)` can be also used as a convenient shortcut for\n",
    "`tqdm(xrange(N))`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import trange\n",
    "for i in trange(10000, unit_scale=True, desc=\"hello\", unit=\"epoch\"):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Screenshot](https://img.tqdm.ml/tqdm.gif)|[![Video](https://img.tqdm.ml/video.jpg)](https://tqdm.github.io/video) [![Slides](https://img.tqdm.ml/slides.jpg)](https://tqdm.github.io/PyData2019/slides.html) [![Merch](https://img.tqdm.ml/merch.jpg)](https://tqdm.github.io/merch)\n",
    "-|-\n",
    "\n",
    "It can also be executed as a module with pipes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! seq 9999999 | tqdm --bytes | wc -l"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```sh\n",
    "tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` > backup.tgz\n",
    " 44%|██████████████▊                   | 153M/352M [00:14<00:18, 11.0MB/s]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overhead is low -- about 60ns per iteration (80ns with `tqdm.gui`), and\n",
    "is unit tested against performance regression. By comparison, the\n",
    "well-established\n",
    "[ProgressBar](https://github.com/niltonvolpato/python-progressbar) has\n",
    "an 800ns/iter overhead.\n",
    "\n",
    "In addition to its low overhead, `tqdm` uses smart algorithms to predict\n",
    "the remaining time and to skip unnecessary iteration displays, which\n",
    "allows for a negligible overhead in most cases.\n",
    "\n",
    "`tqdm` works on any platform (Linux, Windows, Mac, FreeBSD, NetBSD,\n",
    "Solaris/SunOS), in any console or in a GUI, and is also friendly with\n",
    "IPython/Jupyter notebooks.\n",
    "\n",
    "`tqdm` does not require any dependencies (not even `curses`!), just\n",
    "Python and an environment supporting `carriage return \\r` and\n",
    "`line feed \\n` control characters.\n",
    "\n",
    "---\n",
    "\n",
    "## Usage\n",
    "\n",
    "`tqdm` is very versatile and can be used in a number of ways.\n",
    "The three main ones are given below.\n",
    "\n",
    "### Iterable-based\n",
    "\n",
    "Wrap `tqdm()` around any iterable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "from time import sleep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "text = \"\"\n",
    "for char in tqdm([\"a\", \"b\", \"c\", \"d\"]):\n",
    "    sleep(0.25)\n",
    "    text = text + char"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`trange(i)` is a special optimised instance of `tqdm(range(i))`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import trange\n",
    "\n",
    "for i in trange(100):\n",
    "    sleep(0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Instantiation outside of the loop allows for manual control over `tqdm()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pbar = tqdm([\"a\", \"b\", \"c\", \"d\"])\n",
    "for char in pbar:\n",
    "    sleep(0.25)\n",
    "    pbar.set_description(\"Processing %s\" % char)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Manual\n",
    "\n",
    "Manual control of `tqdm()` updates using a `with` statement:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with tqdm(total=100) as pbar:\n",
    "    for i in range(10):\n",
    "        sleep(0.1)\n",
    "        pbar.update(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the optional variable `total` (or an iterable with `len()`) is\n",
    "provided, predictive stats are displayed.\n",
    "\n",
    "`with` is also optional (you can just assign `tqdm()` to a variable,\n",
    "but in this case don't forget to `del` or `close()` at the end:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pbar = tqdm(total=100)\n",
    "for i in range(10):\n",
    "    sleep(0.1)\n",
    "    pbar.update(10)\n",
    "pbar.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Module"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perhaps the most wonderful use of `tqdm` is in a script or on the\n",
    "command line. Simply inserting `tqdm` (or `python -m tqdm`) between\n",
    "pipes will pass through all `stdin` to `stdout` while printing progress\n",
    "to `stderr`.\n",
    "\n",
    "The example below demonstrated counting the number of lines in all\n",
    "Python files in the current directory, with timing information included."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! time find . -name '*.py' -type f -exec cat \\{} \\; | wc -l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! time find . -name '*.py' -type f -exec cat \\{} \\; | tqdm | wc -l"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the usual arguments for `tqdm` can also be specified."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! find . -name '*.py' -type f -exec cat \\{} \\; | tqdm --unit loc --unit-scale --total 4104300 --null"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Backing up a large directory?\n",
    "\n",
    "```sh\n",
    "tar -zcf - docs/ | tqdm --bytes --total `du -sb docs/ | cut -f1` > backup.tgz\n",
    " 44%|██████████████▊                   | 153M/352M [00:14<00:18, 11.0MB/s]\n",
    "```\n",
    "\n",
    "This can be beautified further:\n",
    "\n",
    "```sh\n",
    "BYTES=\"$(du -sb docs/ | cut -f1)\"\n",
    "tar -cf - docs/ \\\n",
    "  | tqdm --bytes --total \"$BYTES\" --desc Processing | gzip \\\n",
    "  | tqdm --bytes --total \"$BYTES\" --desc Compressed --position 1 \\\n",
    "  > ~/backup.tgz\n",
    "Processing: 100%|██████████████████████| 352M/352M [00:14<00:00, 30.2MB/s]\n",
    "Compressed:  42%|█████████▎            | 148M/352M [00:14<00:19, 10.9MB/s]\n",
    "```\n",
    "\n",
    "Or done on a file level using 7-zip:\n",
    "\n",
    "```sh\n",
    "7z a -bd -r backup.7z docs/ | grep Compressing \\\n",
    "  | tqdm --total $(find docs/ -type f | wc -l) --unit files \\\n",
    "  | grep -v Compressing\n",
    "100%|██████████████████████████▉| 15327/15327 [01:00<00:00, 712.96files/s]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tqdm?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! tqdm --help"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples and Advance Usage\n",
    "\n",
    "- See the [examples](https://github.com/tqdm/tqdm/tree/master/examples)\n",
    "  folder;\n",
    "- import the module and run `help()`;\n",
    "- consult the [wiki](https://github.com/tqdm/tqdm/wiki)\n",
    "    - this has an\n",
    "      [excellent article](https://github.com/tqdm/tqdm/wiki/How-to-make-a-great-Progress-Bar)\n",
    "      on how to make a **great** progressbar;\n",
    "- check out the [slides from PyData London](https://tqdm.github.io/PyData2019/slides.html), or\n",
    "- run this file!\n",
    "\n",
    "### Description and additional stats\n",
    "\n",
    "Custom information can be displayed and updated dynamically on `tqdm` bars\n",
    "with the `desc` and `postfix` arguments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm, trange\n",
    "from random import random, randint\n",
    "from time import sleep\n",
    "\n",
    "with trange(10) as t:\n",
    "    for i in t:\n",
    "        # Description will be displayed on the left\n",
    "        t.set_description('GEN %i' % i)\n",
    "        # Postfix will be displayed on the right,\n",
    "        # formatted automatically based on argument's datatype\n",
    "        t.set_postfix(loss=random(), gen=randint(1,999), str='h',\n",
    "                      lst=[1, 2])\n",
    "        sleep(0.1)\n",
    "\n",
    "with tqdm(total=10, bar_format=\"{postfix[0]} {postfix[1][value]:>8.2g}\",\n",
    "          postfix=[\"Batch\", dict(value=0)]) as t:\n",
    "    for i in range(10):\n",
    "        sleep(0.1)\n",
    "        t.postfix[1][\"value\"] = i / 2\n",
    "        t.update()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Points to remember when using `{postfix[...]}` in the `bar_format` string:\n",
    "\n",
    "- `postfix` also needs to be passed as an initial argument in a\n",
    "  compatible format, and\n",
    "- `postfix` will be auto-converted to a string if it is a `dict`-like\n",
    "  object. To prevent this behaviour, insert an extra item into the\n",
    "  dictionary where the key is not a string.\n",
    "\n",
    "Additional `bar_format` parameters may also be defined by overriding\n",
    "`format_dict`, and the bar itself may be modified using `ascii`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "from time import sleep\n",
    "\n",
    "class TqdmExtraFormat(tqdm):\n",
    "    \"\"\"Provides a `total_time` format parameter\"\"\"\n",
    "    @property\n",
    "    def format_dict(self):\n",
    "        d = super(TqdmExtraFormat, self).format_dict\n",
    "        total_time = d[\"elapsed\"] * (d[\"total\"] or 0) / max(d[\"n\"], 1)\n",
    "        d.update(total_time=self.format_interval(total_time) + \" in total\")\n",
    "        return d\n",
    "\n",
    "for i in TqdmExtraFormat(\n",
    "      range(9), ascii=\" .oO0\",\n",
    "      bar_format=\"{total_time}: {percentage:.0f}%|{bar}{r_bar}\"):\n",
    "    if i == 4:\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that `{bar}` also supports a format specifier `[width][type]`.\n",
    "\n",
    "- `width`\n",
    "    + unspecified (default): automatic to fill `ncols`\n",
    "    + `int >= 0`: fixed width overriding `ncols` logic\n",
    "    + `int < 0`: subtract from the automatic default\n",
    "- `type`\n",
    "    + `a`: ascii (`ascii=True` override)\n",
    "    + `u`: unicode (`ascii=False` override)\n",
    "    + `b`: blank (`ascii=\"  \"` override)\n",
    "\n",
    "This means a fixed bar with right-justified text may be created by\n",
    "using: `bar_format=\"{l_bar}{bar:10}|{bar:-10b}right-justified\"`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nested progress bars\n",
    "\n",
    "`tqdm` supports nested progress bars. Here's an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm.auto import trange\n",
    "from time import sleep\n",
    "\n",
    "for i in trange(4, desc='1st loop'):\n",
    "    for j in trange(5, desc='2nd loop'):\n",
    "        for k in trange(50, desc='3rd loop', leave=False):\n",
    "            sleep(0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For manual control over positioning (e.g. for multi-processing use),\n",
    "you may specify `position=n` where `n=0` for the outermost bar, `n=1`\n",
    "for the next, and so on. However, it's best to check if tqdm can work\n",
    "without manual position first.\n",
    "\n",
    "```python\n",
    "from time import sleep\n",
    "from tqdm import trange, tqdm\n",
    "from multiprocessing import Pool, RLock, freeze_support\n",
    "\n",
    "L = list(range(9))\n",
    "\n",
    "def progresser(n):\n",
    "    interval = 0.001 / (n + 2)\n",
    "    total = 5000\n",
    "    text = \"#{}, est. {:<04.2}s\".format(n, interval * total)\n",
    "    for _ in trange(total, desc=text, position=n):\n",
    "        sleep(interval)\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    freeze_support()  # for Windows support\n",
    "    tqdm.set_lock(RLock())  # for managing output contention\n",
    "    p = Pool(initializer=tqdm.set_lock, initargs=(tqdm.get_lock(),))\n",
    "    p.map(progresser, L)\n",
    "```\n",
    "\n",
    "Note that in Python 3, `tqdm.write` is thread-safe:\n",
    "\n",
    "```python\n",
    "from time import sleep\n",
    "from tqdm import tqdm, trange\n",
    "from concurrent.futures import ThreadPoolExecutor\n",
    "\n",
    "L = list(range(9))\n",
    "\n",
    "def progresser(n):\n",
    "    interval = 0.001 / (n + 2)\n",
    "    total = 5000\n",
    "    text = \"#{}, est. {:<04.2}s\".format(n, interval * total)\n",
    "    for _ in trange(total, desc=text):\n",
    "        sleep(interval).auto\n",
    "    if n == 6:\n",
    "        tqdm.write(\"n == 6 completed.\")\n",
    "        tqdm.write(\"`tqdm.write()` is thread-safe in py3!\")\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    with ThreadPoolExecutor() as p:\n",
    "        p.map(progresser, L)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hooks and callbacks\n",
    "\n",
    "`tqdm` can easily support callbacks/hooks and manual updates.\n",
    "Here's an example with `urllib`:\n",
    "\n",
    "**`urllib.urlretrieve` documentation**\n",
    "\n",
    "> [...]\n",
    "> If present, the hook function will be called once\n",
    "> on establishment of the network connection and once after each block read\n",
    "> thereafter. The hook will be passed three arguments; a count of blocks\n",
    "> transferred so far, a block size in bytes, and the total size of the file.\n",
    "> [...]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib, os\n",
    "from tqdm import tqdm\n",
    "urllib = getattr(urllib, 'request', urllib)\n",
    "\n",
    "class TqdmUpTo(tqdm):\n",
    "    \"\"\"Provides `update_to(n)` which uses `tqdm.update(delta_n)`.\"\"\"\n",
    "    def update_to(self, b=1, bsize=1, tsize=None):\n",
    "        \"\"\"\n",
    "        b  : int, optional\n",
    "            Number of blocks transferred so far [default: 1].\n",
    "        bsize  : int, optional\n",
    "            Size of each block (in tqdm units) [default: 1].\n",
    "        tsize  : int, optional\n",
    "            Total size (in tqdm units). If [default: None] remains unchanged.\n",
    "        \"\"\"\n",
    "        if tsize is not None:\n",
    "            self.total = tsize\n",
    "        return self.update(b * bsize - self.n)  # also sets self.n = b * bsize\n",
    "\n",
    "eg_link = \"https://caspersci.uk.to/matryoshka.zip\"\n",
    "with TqdmUpTo(unit='B', unit_scale=True, unit_divisor=1024, miniters=1,\n",
    "              desc=eg_link.split('/')[-1]) as t:  # all optional kwargs\n",
    "    urllib.urlretrieve(eg_link, filename=os.devnull,\n",
    "                       reporthook=t.update_to, data=None)\n",
    "    t.total = t.n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspired by [twine#242](https://github.com/pypa/twine/pull/242).\n",
    "Functional alternative in\n",
    "[examples/tqdm_wget.py](https://github.com/tqdm/tqdm/blob/master/examples/tqdm_wget.py).\n",
    "\n",
    "It is recommend to use `miniters=1` whenever there is potentially large\n",
    "differences in iteration speed (e.g. downloading a file over a patchy\n",
    "connection).\n",
    "\n",
    "**Wrapping read/write methods**\n",
    "\n",
    "To measure throughput through a file-like object's `read` or `write`\n",
    "methods, use `CallbackIOWrapper`:\n",
    "\n",
    "```python\n",
    "from tqdm import tqdm\n",
    "from tqdm.utils import CallbackIOWrapper\n",
    "\n",
    "with tqdm(total=file_obj.size,\n",
    "          unit='B', unit_scale=True, unit_divisor=1024) as t:\n",
    "    fobj = CallbackIOWrapper(t.update, file_obj, \"read\")\n",
    "    while True:\n",
    "        chunk = fobj.read(chunk_size)\n",
    "        if not chunk:\n",
    "            break\n",
    "    t.reset()\n",
    "    # ... continue to use `t` for something else\n",
    "```\n",
    "\n",
    "Alternatively, use the even simpler `wrapattr` convenience function,\n",
    "which would condense both the `urllib` and `CallbackIOWrapper` examples\n",
    "down to:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib, os\n",
    "from tqdm import tqdm\n",
    "\n",
    "eg_link = \"https://caspersci.uk.to/matryoshka.zip\"\n",
    "response = getattr(urllib, 'request', urllib).urlopen(eg_link)\n",
    "with tqdm.wrapattr(open(os.devnull, \"wb\"), \"write\",\n",
    "                   miniters=1, desc=eg_link.split('/')[-1],\n",
    "                   total=getattr(response, 'length', None)) as fout:\n",
    "    for chunk in response:\n",
    "        fout.write(chunk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `requests` equivalent is nearly identical:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests, os\n",
    "from tqdm import tqdm\n",
    "\n",
    "eg_link = \"https://caspersci.uk.to/matryoshka.zip\"\n",
    "response = requests.get(eg_link, stream=True)\n",
    "with tqdm.wrapattr(open(os.devnull, \"wb\"), \"write\",\n",
    "                   miniters=1, desc=eg_link.split('/')[-1],\n",
    "                   total=int(response.headers.get('content-length', 0))) as fout:\n",
    "    for chunk in response.iter_content(chunk_size=4096):\n",
    "        fout.write(chunk)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pandas Integration\n",
    "\n",
    "Due to popular demand we've added support for `pandas` -- here's an example\n",
    "for `DataFrame.progress_apply` and `DataFrameGroupBy.progress_apply`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "\n",
    "df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))\n",
    "\n",
    "# Register `pandas.progress_apply` and `pandas.Series.map_apply` with `tqdm`\n",
    "# (can use `tqdm.gui.tqdm`, `tqdm.notebook.tqdm`, optional kwargs, etc.)\n",
    "tqdm.pandas(desc=\"my bar!\")\n",
    "\n",
    "# Now you can use `progress_apply` instead of `apply`\n",
    "# and `progress_map` instead of `map`\n",
    "df.progress_apply(lambda x: x**2)\n",
    "# can also groupby:\n",
    "# df.groupby(0).progress_apply(lambda x: x**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In case you're interested in how this works (and how to modify it for\n",
    "your own callbacks), see the\n",
    "[examples](https://github.com/tqdm/tqdm/tree/master/examples) folder or\n",
    "import the module and run `help()`.\n",
    "\n",
    "### Keras Integration\n",
    "\n",
    "A `keras` callback is also available:\n",
    "\n",
    "```python\n",
    "from tqdm.keras import TqdmCallback\n",
    "\n",
    "...\n",
    "\n",
    "model.fit(..., verbose=0, callbacks=[TqdmCallback()])\n",
    "```\n",
    "\n",
    "### IPython/Jupyter Integration\n",
    "\n",
    "IPython/Jupyter is supported via the `tqdm.notebook` submodule:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm.notebook import trange, tqdm\n",
    "from time import sleep\n",
    "\n",
    "for i in trange(3, desc='1st loop'):\n",
    "    for j in tqdm(range(100), desc='2nd loop'):\n",
    "        sleep(0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to `tqdm` features, the submodule provides a native Jupyter\n",
    "widget (compatible with IPython v1-v4 and Jupyter), fully working nested\n",
    "bars and colour hints (blue: normal, green: completed, red:\n",
    "error/interrupt, light blue: no ETA); as demonstrated below.\n",
    "\n",
    "![Screenshot-Jupyter3](https://img.tqdm.ml/jupyter-3.gif)\n",
    "\n",
    "The `notebook` version supports percentage or pixels for overall width\n",
    "(e.g.: `ncols='100%'` or `ncols='480px'`).\n",
    "\n",
    "It is also possible to let `tqdm` automatically choose between console\n",
    "or notebook versions by using the `autonotebook` submodule:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm.autonotebook import tqdm\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that this will issue a `TqdmExperimentalWarning` if run in a\n",
    "notebook since it is not meant to be possible to distinguish between\n",
    "`jupyter notebook` and `jupyter console`. Use `auto` instead of\n",
    "`autonotebook` to suppress this warning.\n",
    "\n",
    "Note that notebooks will display the bar in the cell where it was\n",
    "created. This may be a different cell from the one where it is used. If\n",
    "this is not desired, the creation of the bar must be delayed/moved to\n",
    "the cell where it is desired to be displayed.\n",
    "\n",
    "Another possibility is to have a single bar (near the top of the\n",
    "notebook) which is constantly re-used (using `reset()` rather than\n",
    "`close()`). For this reason, the notebook version (unlike the CLI\n",
    "version) does not automatically call `close()` upon `Exception`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm.notebook import tqdm\n",
    "pbar = tqdm()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# different cell\n",
    "iterable = range(100)\n",
    "pbar.reset(total=len(iterable))  # initialise with new `total`\n",
    "for i in iterable:\n",
    "    pbar.update()\n",
    "pbar.refresh()  # force print final status but don't `close()`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Writing messages\n",
    "\n",
    "This is a work in progress (see\n",
    "[#737](https://github.com/tqdm/tqdm/issues/737)).\n",
    "\n",
    "Since `tqdm` uses a simple printing mechanism to display progress bars,\n",
    "you should not write any message in the terminal using `print()` while a\n",
    "progressbar is open.\n",
    "\n",
    "To write messages in the terminal without any collision with `tqdm` bar\n",
    "display, a `.write()` method is provided:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm.auto import tqdm, trange\n",
    "from time import sleep\n",
    "\n",
    "bar = trange(10)\n",
    "for i in bar:\n",
    "    # Print using tqdm class method .write()\n",
    "    sleep(0.1)\n",
    "    if not (i % 3):\n",
    "        tqdm.write(\"Done task %i\" % i)\n",
    "    # Can also use bar.write()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, this will print to standard output `sys.stdout`. but you can\n",
    "specify any file-like object using the `file` argument. For example,\n",
    "this can be used to redirect the messages writing to a log file or class.\n",
    "\n",
    "[![README-Hits](https://caspersci.uk.to/cgi-bin/hits.cgi?q=tqdm&style=social&r=https://github.com/tqdm/tqdm&l=https://img.tqdm.ml/favicon.png&f=https://img.tqdm.ml/logo.gif)](https://caspersci.uk.to/cgi-bin/hits.cgi?q=tqdm&a=plot&r=https://github.com/tqdm/tqdm&l=https://img.tqdm.ml/favicon.png&f=https://img.tqdm.ml/logo.gif&style=social)|(Since 19 May 2016)\n",
    "-|-"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Do your own experiments here 👇\n",
    "\n",
    "Try `tqdm` youself by adding your code below and running your own experiments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tqdm\n",
    "\n",
    "# your code here\n",
    "tqdm."
   ]
  }
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